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Min, Wookhee; Frankosky, Megan H.; Mott, Bradford W.; Rowe, Jonathan P.; Smith, Andy; Wiebe, Eric; Boyer, Kristy Elizabeth; Lester, James C. – IEEE Transactions on Learning Technologies, 2020
A distinctive feature of game-based learning environments is their capacity for enabling stealth assessment. Stealth assessment analyzes a stream of fine-grained student interaction data from a game-based learning environment to dynamically draw inferences about students' competencies through evidence-centered design. In evidence-centered design,…
Descriptors: Game Based Learning, Student Evaluation, Artificial Intelligence, Models
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Henderson, Nathan; Kumaran, Vikram; Min, Wookhee; Mott, Bradford; Wu, Ziwei; Boulden, Danielle; Lord, Trudi; Reichsman, Frieda; Dorsey, Chad; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2020
In recent years, game-based learning has shown significant promise for creating engaging and effective learning experiences. Developing models that can predict whether students will struggle with mastering certain concepts could guide adaptive support to assist students with mastering those concepts. Game-based learning environments offer…
Descriptors: Competency Based Education, Game Based Learning, Student Evaluation, Evaluation Methods
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Rachmatullah, Arif; Reichsman, Frieda; Lord, Trudi; Dorsey, Chad; Mott, Bradford; Lester, James; Wiebe, Eric – Journal of Science Education and Technology, 2021
This study examined students' genetics learning in a game-based environment by exploring the connections between the expectancy-value theory of achievement motivation and flow theory. A total of 394 secondary school students were recruited and learned genetics concepts through interacting with a game-based learning environment. We measured their…
Descriptors: Models, Secondary School Students, Genetics, Game Based Learning